Advanced University Mathematics (Research and Applications) Program

A four-year, full-time programme in mathematical sciences at Cheenta Academy of Mathematical Sciences, Kolkata. Preparing young mathematicians for fundamental and industry-focused research, including leading PhD programmes worldwide.

The Programme

This four-year programme prepares young mathematicians for fundamental or industry-focused research, with a strong inclination to expose them to both tracks. Graduates are positioned for academic and industrial research opportunities, including leading PhD programmes in the United States, Europe, China, India, and the world's other leading seats of mathematical research.
The programme has a special focus on rural talent — students from outside metropolitan centres who are motivated to learn mathematical sciences and contribute to solving new problems. Identifying and supporting such students is a core institutional commitment.

Programme Components

Five integrated components across all eight semesters.

Pure Mathematics

Group Theory, Rings and Fields, Analysis, Linear Algebra, Vector Calculus, Complex Analysis, Manifolds, Topology, and Functional Analysis, with electives in Differential Geometry, Probability Theory, and Measure Theory. The track prioritises depth and problem-solving over breadth.

Specialization with Research Projects

Machine Learning and Computational Mathematics in Year 1. From Year 2: Machine Learning, Computer Vision, Computational Mathematics, Statistics, Geometric Group Theory, LEAN 4 (Formalization and Auto Formalization), and Neural Networks and Gravitational Physics. Two undergraduate publications are targeted.

Contest Mentoring

Three hours per week for TIFR, ISI M.Math, IIT-JAM, Subject GRE, General GRE, and college-level olympiads including Madhava, IMC, and the Simon Marais Mathematics Competition (SMMC).

Teaching Assistantship & Research Internship

Six hours per week of Teaching Assistantship at Cheenta Academy and six hours per week of Research Internship with collaborating businesses, research groups, or non-profits, from Semester 2 onwards. All engagements are stipended.

Graduate School Mentoring

Mentoring for the GRE Subject Test, graduate school applications, statement of purpose, recommendations, and conference participation, intensifying in Year 4.

Curriculum

Eight semesters of pure mathematics papers, research specialization, and engagement components.
Year / Semester
Pure Mathematics I
Pure Mathematics II
Research Specialization
Engagement
Year 1Semester 1
Group Theory I
Vector Calculus
Machine Learning (mandatory)
Teaching Assistantship — 12 hours
Year 1Semester 2
Linear Algebra I
Real Analysis I
Computational Mathematics (mandatory)
TA 6h + Research Internship 6h
Year 2Semester 3
Group Theory II
Topology of Metric Spaces
Machine Learning · Computer Vision · Computational Mathematics · Statistics · Geometric Group Theory · LEAN 4 (Formalization & Auto Formalization) · Neural Networks & Gravitational Physics
TA 6h + Research Internship 6h
Year 2Semester 4
Manifolds
Rings, Fields and Modules I
Machine Learning · Computer Vision · Computational Mathematics · Statistics · Geometric Group Theory · LEAN 4 (Formalization & Auto Formalization) · Neural Networks & Gravitational Physics
TA 6h + Research Internship 6h
Year 3Semester 5
Real Analysis II
Rings, Fields and Modules II
Machine Learning · Computer Vision · Computational Mathematics · Statistics · Geometric Group Theory · LEAN 4 (Formalization & Auto Formalization) · Neural Networks & Gravitational Physics
TA 6h + Research Internship 6h
Year 3Semester 6
Point Set Topology
Complex Analysis
Machine Learning · Computer Vision · Computational Mathematics · Statistics · Geometric Group Theory · LEAN 4 (Formalization & Auto Formalization) · Neural Networks & Gravitational Physics
TA 6h + Research Internship 6h
Year 4Semester 7
Algebraic Topology
Elective — Differential Geometry / Probability Theory / Measure Theory
Machine Learning · Computer Vision · Computational Mathematics · Statistics · Geometric Group Theory · LEAN 4 (Formalization & Auto Formalization) · Neural Networks & Gravitational Physics
TA 6h + Research Internship 6h
Year 4Semester 8
Functional Analysis
Elective — Differential Geometry / Probability Theory / Measure Theory
Machine Learning · Computer Vision · Computational Mathematics · Statistics · Geometric Group Theory · LEAN 4 (Formalization & Auto Formalization) · Neural Networks & Gravitational Physics
TA 6h + Research Internship 6h

In Year 1, all students take Machine Learning (Semester 1) and Computational Mathematics (Semester 2) as mandatory foundational papers. From Semester 3, students declare a research specialization from the full list of seven tracks. Research is coupled to the declared specialization; the first publication is targeted by the end of Year 2 and the second as the senior thesis in Year 4. Students enrol in parallel in a traditional undergraduate programme in Kolkata or with an open university.

Faculty

Dr. Ashani Dasgupta

PhD in Mathematics, University of Wisconsin–Milwaukee

Dr. Nitesh Bhardwaj

PhD in Physics, Bielefeld University

Dr. Sankhadip Chakraborty

PhD in Mathematics, IMPA

Srijit Mukherjee

Doctoral Scholar, Pennsylvania State University

Raghunath J.V.

Doctoral Scholar, University of Tennessee

Shayeef Murshid

Doctoral Scholar, Indian Statistical Institute

Visiting Faculty

Dr. Arka Banerjee

Assistant Professor, Vivekananda University; PhD in Mathematics, University of Wisconsin–Milwaukee

Dr. Debajyoti Biswas

Assistant Professor, Shiv Nadar University Chennai; PhD and M.S. from IIT Madras

Apply for the September 2026 Cohort

Applications are reviewed on a rolling basis. The programme is available only offline in Kolkata. Submit your details below, or write to talent@cheenta.org with a CV and cover letter.
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